Process industries have developed various approaches to optimize or improve manufacturing (e.g., reducing manufacturing costs while improving manufacturing yield) in efforts to remain competitive in an ever increasing global economy. One approach has been to base process control limits on estimated or historical process capabilities. An additional approach is to set control limits based on a set of design rules that represent the most aggressive requirements allowed on the process technology.
Although the present approaches have assisted the optimization of process control, the approaches are limited under certain circumstances. First, basing process control limits on perceived tool or process capabilities is disadvantageous for the tool or process capabilities may not be sufficient to avoid yield loss or address reliability issues. For example, with such approach, process control limits often do not get modified until problems are encountered in high volume production. Thus, such limitation may have significant financial impact on manufacturing including the inability to meet customer delivery schedules. Further, the approach of setting control limits based on a set of design rules is unfavorable because the derivation of the process specification limits may be extremely time-consuming for such process is typically performed manually. In addition, adjustments for process exceptions that allow less or require more stringent requirements are also most often performed manually and thus, may be time intensive. Moreover, such adjustments are not usually made until either a yield or manufacturing constraint is encountered.
Therefore, it would be desirable to provide a method of determining and optimizing process control limits which allow the process control limits to be modified sufficiently to reduce yield loss or reliability issues.